4D-GSW: 4D高斯点散布的运动感知空间-时间一致水印技术
4D-GSW: Kinematic-Aware Spatio-Temporal Consistent Watermarking for 4D Gaussian Splatting
AI总结：
本文提出4D-GSW，一种运动感知的空间-时间一致水印技术，用于在4D高斯点散布中嵌入鲁棒的版权信息，同时保持高空间-时间一致性。
摘要：
尽管4D高斯点散布（4DGS）已革新了高保真的动态重建，但保护这些资产的知识产权仍是一个开放性挑战。传统隐写技术常常忽视底层的运动流形，导致非物理的伪影，如严重的时序闪烁和"FVD崩溃"。为了解决这个问题，我们提出了4D-GSW，一种运动感知的水印框架，旨在嵌入鲁棒的版权信息同时保持高空间-时间一致性。与以往的4D隐写技术不同，我们的方法明确处理运动轨迹的物理一致性。我们引入了空间-时间曲率（STC）度量来识别"动态瞬间"，并自适应地门控水印梯度注入，以保护关键运动流形免受非物理扰动。为了确保复杂变形中的全局一致性，我们提出了联合HMM-MRF能量最小化模型，该模型同步水印相位在时间轨迹和空间邻域内。此外，一种各向异性梯度路由机制确保水印嵌入严格脱离光度重建保真度。大量实验表明，我们的方法在鲁棒隐藏水印的同时，能够抵抗各种攻击并保持高质量的渲染质量和空间-时间一致性。
英文摘要：
While 4D Gaussian Splatting (4DGS) has revolutionized high-fidelity dynamic reconstruction, safeguarding the intellectual property of these assets remains an open challenge. Conventional steganographic techniques often neglect the underlying kinematic manifolds, triggering non-physical artifacts such as severe temporal flickering and "FVD collapse". To address this, we propose \textbf{4D-GSW}, a kinematic-aware watermarking framework designed to embed robust copyright information while preserving high spatio-temporal consistency. Unlike prior 4D steganography that primarily focuses on opacity-guided invisibility, our approach explicitly addresses the physical coherence of motion trajectories. We introduce a \textbf{Spatio-Temporal Curvature (STC)} metric to identify "Dynamic Instants," adaptively gating watermark gradient injection to shield critical motion manifolds from non-physical perturbations. To ensure global coherence across complex deformations, we formulate a joint \textbf{HMM-MRF energy minimization} model that synchronizes watermark phases within both temporal trajectories and spatial neighborhoods. Furthermore, an \textbf{anisotropic gradient routing} mechanism ensures that watermark embedding remains strictly decoupled from photometric reconstruction fidelity. Extensive experiments have demonstrated the superior performance of our method in robustly hiding watermarks while resisting various attacks and maintaining high rendering quality and spatiotemporal consistency.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
